摘要
脉冲耦合神经网络PCNN以其在图像分割、目标识别等领域的独特优势而成为当前的研究热点。本文对其在红外与可见光图像融合领域的应用进行了研究,并针对传统脉冲耦合神经网络参数无法自动设定的难题,提出了基于修正PCNN的参数自动设定方案。针对可见光与红外图像融合的大量实验结果表明,本文方法无论在主观视觉效果还是客观评价参数上均明显优于基于多分辨分析的融合算法,对于拓宽PCNN的应用领域有一定价值。
The Pulse Coupled Neural Network （PCNN） model of the cat visual cortex has proven to have interesting properties in image processing,including segmentation, target recognition et al. This paper proposes a multisensor image fusion scheme based on the modified PCNN. Focusing on the famous difficult problem of PCNN and how to determine PCNN parameters adaptively, this paper brings forward an adaptive PCNN parameters determination algorithm based on water area. Experimental results demonstrate that the proposed fusion scheme outperforms the multiscale decomposition based fusion approaches,both in visual effect and objective evaluation criteria. The research fruits have certain value on the theory research and practical application of PCNN.
出处
《计算机工程与科学》
CSCD
北大核心
2012年第9期83-87,共5页
Computer Engineering & Science
基金
国家自然科学基金资助项目(61102170)
关键词
多传感器图像融合
脉冲耦合神经网络
参数设定
客观评价准则
multisensor image fusion
pulse-coupled neural network （PCNN）
parameter determination
objective evaluation criteria
